Open AccessA RESPONSE TO WHITE AND GORARD: AGAINST INFERENTIAL STATISTICS: HOW AND WHY CURRENT STATISTICS TEACHING GETS IT WRONG
Author(s) -
James Nicholson,
Jim Ridgway
Publication year - 2017
Publication title -
statistics education research journal
Language(s) - English
Resource type - Journals
ISSN - 1570-1824
DOI - 10.52041/serj.v16i1.216
Subject(s) - statistical inference , statistical hypothesis testing , statistics , statistics education , psychology , statistical analysis , frequentist probability , statistical thinking , argument (complex analysis) , mathematics education , mathematics , bayesian probability , biochemistry , chemistry
White and Gorard make important and relevant criticisms of some of the methods commonly used in social science research, but go further by criticising the logical basis for inferential statistical tests. This paper comments briefly on matters we broadly agree on with them and more fully on matters where we disagree. We agree that too little attention is paid to the assumptions underlying inferential statistical tests, to the design of studies, and that p-values are often misinterpreted. We show why we believe their argument concerning the logic of inferential statistical tests is flawed, and how White and Gorard misrepresent the protocols of inferential statistical tests, and make brief suggestions for rebalancing the statistics curriculum.
First published May 2017 at Statistics Education Research Journal Archives